Method and apparatus for range derivation in context adaptive binary arithmetic coding

ABSTRACT

A method and apparatus of entropy coding of coding symbols using Context-Based Adaptive Binary Arithmetic Coder (CABAC) are disclosed. The method operates by applying context-adaptive arithmetic encoding or decoding to a current bin of a binary data of a current coding symbol according to a current binarized probability value of the current bin and a current range associated with a current state of the context-adaptive arithmetic encoding or decoding; deriving an LPS probability index corresponding to an inverted current binarized probability value or the current binarized probability value, depending on whether the current binarized probability value of the current bin is greater than or equal to 2 k−1 , k being a positive integer; deriving a range index for identifying one range interval containing the current range; and deriving an LPS range using one or more mathematical operations.

CROSS REFERENCE TO RELATED APPLICATIONS

The present invention is a continuation of pending U.S. patent application Ser. No. 16/629,440, filed on Jan. 8, 2020, which is a 371 National Phase of PCT Application No. PCT/CN2018/095419, filed on Jul. 12, 2018, which claims priority to U.S. Provisional Patent Application Ser. No. 62/532,389, filed on Jul. 14, 2017, U.S. Provisional Patent Application Ser. No. 62/670,614, filed on May 11, 2018, U.S. Provisional Patent Application Ser. No. 62/678,343, filed on May 31, 2018 and U.S. Provisional Patent Application Ser. No. 62/693,497, filed on Jul. 3, 2018. The U.S. Provisional patent application is hereby incorporated by reference in its entirety.

FIELD OF THE INVENTION

The present invention relates to entropy coding techniques for image coding and video coding. In particular, the present invention relates to range derivation for Context-Based Adaptive Binary Arithmetic Coder (CABAC) for image coding and video coding.

BACKGROUND AND RELATED PRIOR ART

The arithmetic coding is known as one of the efficient data compressing methods, and is widely used in coding standards, including JBIG, JPEG2000, H.264/AVC, and High-Efficiency Video Coding (HEVC). In H.264/AVC and HEVC Test Model Version 16.0 (HM-16.0), context-based adaptive binary arithmetic coding (CABAC) is adopted as the entropy coding tool in the video coding system.

As shown in FIG. 1(a), a CABAC encoder consists of three parts: binarization unit 110, context modelling unit 120, and binary arithmetic encoding unit 130. The CABAC encoding process comprises the binarization step, the context modelling step and the binary arithmetic encoding step. In the binarization step, each syntax element is uniquely mapped into a binary string (bin or bins). In the context modelling step, a probability model is selected for each bin. The corresponding probability model may depend on previously encoded syntax elements, bin indexes, and side information. After the binarization and the context model assignment, a bin value along with its associated model is transmitted to the binary arithmetic encoding unit 130 for generating the bitstream. On the other hand, a CABAC decoder receives the bitstream, and performs a CABAC decoding process corresponding to the foregoing CABAC encoding process on the bitstream so as to derive the values of the syntax elements. As shown in FIG. 1(b), a CABAC decoder consists of three parts: de-binarization unit 150, context modelling unit 160, and binary arithmetic decoding unit 140. The CABAC decoding process comprises the binary arithmetic decoding step, the de-binarization step and the context modelling step. In de-binarization step and context modelling step, according to the target decoding syntax element, a probability model is selected for each bin. The corresponding probability model may depend on previously decoded syntax elements, bin indexes, and side information. According to the probability model, a bin value is parsed by the binary arithmetic decoding unit 140. A syntax element is decoded by the de-binarization unit 150.

Binary arithmetic encoding in 130 is a recursive interval-subdividing procedure. The output bitstream is the pointer to the final probability of coding interval. The probability of coding interval, T is specified by range and the lower bound of coding interval (designated as “low” in the following discussion). The range is the possible scope of the coding interval. Depending on whether the current symbol is the most probable symbol (MPS) or the least probable symbol (LPS), the next coding interval is updated as one of the two sub-intervals accordingly, as shown in eq. (1) and eq. (2).

$\begin{matrix} {{range}_{n + 1} = \left\{ \begin{matrix} {{{range}_{n} - {rangeLPS}_{n}},} & {{if}\mspace{14mu}{MPS}} \\ {rangeLPS}_{n,} & {{if}\mspace{14mu}{LPS}} \end{matrix} \right.} & (1) \\ {{low}_{n + 1} = \left\{ {\begin{matrix} {{low}_{n},} & {{if}\mspace{14mu}{MPS}} \\ {{low}_{n} + {range}_{n} - {rangeLPS}_{n}} & {{if}\mspace{14mu}{LPS}} \end{matrix},} \right.} & (2) \end{matrix}$

where rangeLPS is the estimated range when LPS is coded.

FIG. 2 illustrates the concept of the binary arithmetic coding. Initially, the probability range (i.e., range₀) is 1 and the low boundary (i.e., low₀) is 0 as indicated by probability scale 210. If the first symbol is a MPS symbol, a pointer in the lower part of the probability scale 210 may be used to signal the event of an MPS symbol. The range₁ is used as the probability scale 220 for processing the next symbol. Again, the probability scale 220 is divided into two parts for MPS and LPS respectively. If the second symbol is an LPS symbol, the rangeLPS₁ is selected as the probability scale 230 for the next symbol. Every time when a new symbol is coded, the corresponding range becomes smaller. When a range becomes too small, the range can be re-normalized to form a probability scale 240 with larger range.

In modern arithmetic coding, the probability update is often done according to a model. For example, a method is described by Marpe, et al., in a technical publication (“Context-Based Adaptive Binary Arithmetic Coding in the H.264/AVC Video Compression Standard”, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 13, No. 7, pp. 620-636, July 2003), where the following formula is used: p _(new)=(1−α)·y+α·p _(old).  (3)

In the above equation, y is equal to“zero” if current symbol is a most probable symbol (MPS); otherwise, y is equal to “one”. This formula provides an estimated value for probability of the least probable symbol (LPS). The weighting α is derived according to the following equation: α=(min_prob/0.5)^((1/state_number)),  (4)

where min_prob corresponds to the minimum probability of the least probable symbol of CABAC and state_number corresponds to the number of context states for probability value estimation.

For CABAC of HEVC, there are 64 probability states. The min_prob is 0.01875, and the state_number is 63. Each state has a probability value indicating the probability to select the LPS. The 64 representative probability values, P_(σ) ∈[0.01875, 0.5], were derived for the LPS by the following recursive equation: P _(σ) =α·P _(σ-1) for all σ=1, . . . ,63, with α=(0.01875/0.5)^(1/63) and p ₀=0.5  (5)

The rangeLPS value of a state a is derived by the following equation: rangeLPS_(σ)=RANGE×P _(σ)  (6)

To reduce the computations required for deriving rangeLPS, the result of rangeLPS of each range value can be pre-calculated and stored in a lookup table (LUT). In H.264/AVC and HEVC, a 4-column pre-calculated rangeLPS table is adopted to reduce the table size as shown in Table 1. The range is divided into four segments. In each segment, the rangeLPS of each probability state σ (p_(σ)) is pre-defined. In other words, the rangeLPS of a probability state σ is quantized into four values. The rangeLPS selected depends on the segment that the range belongs to.

TABLE 1 (Range >> 6)&3 Sets 0 1 2 3 Range Min 256 320 384 448 Range Max 319 383 447 510 State Range LPS 0 128 176 208 240 1 128 167 197 227 2 128 158 187 216 3 123 150 178 205 4 116 142 169 195 5 111 135 160 185 6 105 128 152 175 7 100 122 144 166 8 95 116 137 158 9 90 110 130 150 10 85 104 123 142 11 81 99 117 135 12 77 94 111 128 13 73 89 105 122 14 69 85 100 116 15 66 80 95 110 16 62 76 90 104 17 59 72 86 99 18 56 69 81 94 19 53 65 77 89 20 51 62 73 85 21 48 59 69 80 22 46 56 66 76 23 43 53 63 72 24 41 50 59 69 25 39 48 56 65 26 37 45 54 62 27 35 43 51 59 28 33 41 48 56 29 32 39 46 53 30 30 37 43 50 31 29 35 41 48 32 27 33 39 45 33 26 31 37 43 34 24 30 35 41 35 23 28 33 39 36 22 27 32 37 37 21 26 30 35 38 20 24 29 33 39 19 23 27 31 40 18 22 26 30 41 17 21 25 28 42 16 20 23 27 43 15 19 22 25 44 14 18 21 24 45 14 17 20 23 46 13 16 19 22 47 12 15 18 21 48 12 14 17 20 49 11 14 16 19 50 11 13 15 18 51 10 12 15 17 52 10 12 14 16 53 9 11 13 15 54 9 11 12 14 55 8 10 12 14 56 8 9 11 13 57 7 9 11 12 58 7 9 10 12 59 7 8 10 11 60 6 8 9 11 61 6 7 9 10 62 6 7 8 9 63 2 2 2 2

In Table 1, “>>” represents the right shift operation. In JCTVC-F254 (Alshin et al., Multi-parameter probability up-date for CABAC, Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11, 6th Meeting: Torino, IT, 14-22 Jul. 2011, Document: JCTVC-F254), Alshin, et al., disclose a multi-parameter probability update for the CABAC of the HEVC standard. The parameter N=1/(1−α) is an approximate measurement for number of previously encoded bins (i.e., “window size”) that have significant influence on the current bin. The choice of parameter N determines sensitivity of the model. A sensitive system will react to real changing quickly. On the other hand, a less sensitive model will not react to noise and random errors. Both properties are useful but contradictory. Accordingly, Alshin, et al., disclose a method to calculate several values with different α_(i) simultaneously: p _(i_new)=(1−α₁)·y+α _(i) ·p _(i_old)  (7)

and use weighted average as next bin probability prediction: p _(new)=Σ(β_(i) ·p _(i_new)),  (8)

where β_(i) is a weighting factor associated with α.

Instead of state transition lookup tables (m_aucNextStateMPS and m_aucNextStateLPS) utilized in CABAC of the AVC standard for updating the state and its corresponding probability, Alshin, et al., use the explicit calculation with multiplication free formula for probability update. Assuming that probability p_(i) is represented by integer number P_(i) from 0 to 2^(k) (i.e., p_(i)=P_(i)/2^(k)) and α_(i) is represented by 1 over a power of two number (i.e., α_(i)=1/2^(M) ^(i) ), multiplication free formula for probability update can be derived as follows: P _(i)=(Y>>M _(i))+P−(P _(i) >>M _(i)).  (9)

This formula predicts probability that next bin will be “1”, where Y=2^(k) if the last coding bin is “1”, Y=0 if the last coding bin is “0”, and “>>M_(i)” corresponds to the right shift by M_(i) bits operation.

To keep balance between complexity increase and performance improvement, it is considered that linear combination for probability estimation consists of only two parameters: P ₀=(Y>>4)+P ₀−(P ₀>>4),  (10) P ₁=(Y>>7)+P ₁−(P ₀>>7), and  (11) P=(P ₀ +P ₁+1)>>1.  (12)

Floating point value that corresponds to probability for AVC CABAC is always less than or equal to ½. If the probability exceeds this limit, LPS becomes MPS to keep probability inside interval mentioned above. It needs MPS/LPS switching when the probability of MPS/LPS is larger than 0.5. Alshin, et al., proposed to increase permissible level of probability (in terms of float-point values) up to 1 to avoid MPS/LPS switching. Therefore, one lookup table (LUT) for storing RangeOne or RangeZero is derived.

In VCEG-AZ07 (Chen, et al., “Further improvements to HMKTA-1.0”, ITU-T Video Coding Experts Group (VCEG) meeting, Warsaw, Poland, IT, 19-26 Jun. 2015, Document: VCEG-AZ07), Chen, et al., proposed to use a single parameter CABAC. The probability derivation is the same as JCTVC-F254, which uses eq. (9) to derive the probability of being one or zero. For each context, only one updating speed is used, which means for each context, only one Nis used. However, different contexts can use different N's. The range for Nis from 4 to 7, and a 2-bit variable is used to indicate the probability updating speed for a specific context model. The N value is determined at the encoder side and signalled in the bitstream.

In JCTVC-F254 and VCEG-AZ07, the LUT of RangeOne or RangeZero is a 64-column by 512-row table. The input of the LUT is current range and the current probability. The valid range of the current range is from 256 to 510. The current range is divided into 64 sections, where each section contains 4 values of current range (e.g. 256 to 259, 260 to 263, etc.). The section index of range can be derived by: rangeIdx=(range>>2)−64, or  (13) rangeIdx=(range>>2)& 63  (14)

The valid range of the current probability (P) is from 0 to 2^(k)−1. In JCTVC-F254 and VCEG-AZ07, the k is 15. The current probability is divided into 512 sections, where each section contains 64 values of current probability (e.g. 0 to 63, 64 to 127, etc.). The section index of probability can be derived by probIdx=(P>>6).  (15)

The RangeOne value can be derived by table lookup, for example RangeOne=tableRangeOne[rangeIdx][probIdx]  (16)

In JCTVC-F254 and VCEG-AZ07, the table size of the tableRangeOne table is 512 rows×64 columns×9-bits. The tableRangeOne covers the probability from 0.0 to 1.0. The size of lookup tables becomes very large. It requires 294912 bits of memory. It is desirable to overcome the issue without degrading the coding performance or increasing the computational complexity noticeably.

BRIEF SUMMARY OF THE INVENTION

A method and apparatus of entropy coding of coding symbols using Context-Based Adaptive Binary Arithmetic Coder (CABAC) are disclosed. According to the present invention, context-adaptive arithmetic encoding or decoding is applied to a current bin of a binary data of a current coding symbol according to a current probability for a binary value of the current bin and a current range associated with a current state of the context-adaptive arithmetic encoding or decoding, where the current probability is generated according to one or more previously coded symbols before the current coding symbol. An LPS probability index corresponding to an inverted current probability or the current probability is derived depending on whether the current probability for the binary value of the current bin is greater than 0.5. A range index is derived for identifying one range interval containing the current range. An LPS range is derived either using one or more mathematical operations comprising calculating a multiplication of a first value related to (2*the LPS probability index+1) or the LPS probability index and a second value related to (2*the range index+1) or the range index, or using a look-up-table to derive the LPS range, the look-up-table includes table contents corresponding to values of LPS range associated with a set of LPS probability indexes and a set of range indexes for encoding or decoding a binary value of the current bin, where the range index corresponds to a result of right-shifting the current range by mm and mm is a non-negative integer and each value of LPS range corresponds to one product of (2*one LPS probability index+1) and (2*one shifted range index+1) or corresponds to a offset and one product of one LPS probability index and one range index.

In one embodiment, when the current probability for the binary value of the current bin is greater than 0.5, an LPS (least-probably-symbol) probability is set equal to (1−the current probability) and otherwise, the LPS probability is set equal to the current probability. The LPS probability index is determined based on a target index indicating one probability interval containing the current probability or the LPS probability.

In another embodiment, when the current probability for the binary value of the current bin is greater than 2^(k−1) or is greater than or equal to 2^(k−1), an LPS probability is set equal to (2^(k)−1−the current probability) and the LPS probability index is set equal to (2^(n+1)−1) minus a result of right-shifting the current probability by (k−n−1) bits. Otherwise, the LPS probability is set equal to the current probability and the LPS probability index is set equal to the result of right-shifting the current probability by (k−n−1) bits, where the current probability is represented by k-bit values, and n and k are positive integers. The LPS range can be derived by multiplying (2*the LPS probability index+1) with (2*the range index+1) to obtain a multiplication result, and right-shifting the multiplication result by x bits and x is a positive integer. For example, k can be equal to 15, n can be equal to 5 and x can be equal to 3. In another example, the LPS range can be derived by multiplying the LPS probability index with the range index to obtain a multiplication result, and right-shifting the multiplication result by x bits plus an offset and x is a positive integer and the offset is an integer. For example, k can be equal to 15, n can be equal to 5, x can be equal to 1 and the offset can be equal to 2, 3, or 4.

The look-up-table may correspond to a two-dimensional table with the LPS probability index as a first table index in a first dimension and a clipped range index as a second table index in a second dimension, where the clipped range index corresponding to the range index. For example, the LPS probability index may have a first value range from 0 to 31, the clipped range index may have a second value range from 0 to 7 and the LPS range may have a third value range from greater than or equal to 0 to smaller than or equal to 255.

In one embodiment, the LPS probability is set equal to a result of bitwise exclusive or (XOR) for a value of (current probability>>(k−1)) and the current probability, or the LPS probability index is set equal to the result of bitwise exclusive or for the value of (current probability>>(k−1)) and the value of (current probability>>(k−n−1)), where the current probability is represented by k-bit values, and n and k are positive integers.

The method may further comprise deriving, from the current range, a rangeOne value and a rangeZero value for the current bin having a value of one and a value of zero respectively, wherein if the current probability for the binary value of the current bin is greater than 0.5 or is greater than or equal to 0.5, the rangeOne value is set to (the current range−the LPS range) and the rangeZero value is set to the LPS range; and otherwise, the rangeZero value is set to (the current range−the LPS range) and the rangeOne value is set to the LPS range.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1(a) and 1(b) illustrate a basic structure of context-based adaptive binary arithmetic coding (CABAC) encoder and decoder.

FIG. 2 illustrates a concept of the binary arithmetic coding, where initially, the probability range (i.e., range₀) is 1 and the low boundary (i.e., low₀) is 0 as indicated by a probability scale.

FIG. 3 illustrates an example of using extended neighbouring blocks for merge candidate list derivation according to JVET-J0058.

FIG. 4 illustrates an example of using extended neighbouring blocks for merge candidate list derivation according to an embodiment of the present invention.

FIG. 5 illustrates an exemplary flowchart of context-based adaptive binary arithmetic coding (CABAC) according to one embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

The following description is of the best-contemplated mode of carrying out the invention. This description is made for the purpose of illustrating the general principles of the invention and should not be taken in a limiting sense. The scope of the invention is best determined by reference to the appended claims.

In JCTVC-F254 and VCEG-AZ07, the rangeOne table covers the probability from 0.0 to 1.0. The LUT of JCTVC-F254 is 144 times of the LUT of HEVC, which is too large to be implemented in terms of hardware cost. Moreover, since the entry value of the RangeOne or RangeZero is derived from the MinRange (i.e., eq. 17), the coding efficiency will be dropped dramatically if a down-sampled LUT is used.

BAC Parameter Initialization

The multi-parameter CABAC disclosed in JCTVC-F254 can improve the coding efficiency of the entropy coding. However, the parameters are fixed as 4 and 7 in eq. (10) and (11). In VCEG-AZ07, the parameter is signalled to fit the probability transition of a target context for target syntax. However, the best parameters might be different for different contexts and also might be different for different slice and different QP. Therefore, method to set the different parameters for different contexts for different QP or different slice is disclosed in the present invention.

The multi-parameter CABAC can be re-formulated as eq. (19) to (21). P ₀=(Y>>α)+P ₀−(P ₀>>α) or P ₀ =P ₀+((Y−P ₀)>α),  (19) P ₁=(Y>>β)+P ₁−(P ₁>>β) or P ₁ =P ₁+((Y−P ₁)>>β),  (20) P=(P ₀ +P ₁+1)>>1  (21)

For different contexts in different QP, the α and β can be different. The α and β can be initialized at context initial process, which is at the beginning of encoding/decoding a slice. The α and β can be derived by a predefined equation and one or more initial values. The initial values can be predefined in the standard. In this invention, some parameter initial methods are proposed.

Method-1: Separate Equation α=((m0*QP+n0)>>o0)+((p0*q0)>>r0)+s0  (22) β=((m1*QP+n1)>>o1)+((p1*q1)>>r1)+s1  (23)

In the above equations, the QP is the slice QP, the m0, n0, o0, p0, q0, r0, s0, m1, n1, o1, p1, q1, r1, and s1 are integer values. Note that, if a variable Y is a negative value, the (X>>Y) means (X<<(−Y)). If the derived α or β is not an integer value, it will be rounded to an integer value. Also, the derived α or β will be clipped within a predefined range.

In one embodiment, the m0, p0, m1, p1 are stored as the initial values for different contexts while the n0, o0, q0, r0, s0, n1, o1, q1, r1, and s1 are fixed values and can be 0.

Method-2: A and Delta Value α=((m0*QP+n0)>>o0)+((p0*q0)>>r0)+s0  (24) delta=((m1*QP+n1)>>o1)+((p1*q1)>>r1)+s1  (25) β=α+delta  (26)

In one embodiment, the QP is the slice QP, the m0, n0, o0, p0, q0, r0, s0, m1, n1, o1, p1, q1, r1, and s1 are the integer values. Note that, if a variable Y is a negative value, the (X>>Y) means (X<<(−Y)). If the derived α, β, or delta is not a integer value, it will be rounded to an integer value. Also, the derived α or β will be clipped within a predefined range.

In one embodiment, the m0, p0, m1, p1 are stored as the initial values for different contexts while the n0, o0, q0, r0, s0, n1, o1, q1, r1, and s1 are fixed values and can be 0. In another embodiment, the m0, p0, m1 are stored as the initial values for different contexts while the n0, o0, q0, s0, n1, o1, p1, q1, r1, and s1 are fixed values and can be 0. In yet another embodiment, the m0, p0, p1 are stored as the initial values for different contexts while the n0, o0, q0, r0, s0, m1, n1, o1, q1, r1, and s1 are fixed values and can be 0.

Method-3: Pair Index

The combination of the α and β can be categorized into several parameter pairs. An index is assigned for a parameter pair. The selected pair index can be derived by a predefined equation and one or more initial values. For example, if range of α and β are within 3 to 8, there are 15 pairs corresponding to:

#1: [3, 4], #2: [3, 5], #3: [3, 6], #4: [3, 7], #5: [3, 8], #6: [4, 5], #7: [4, 6], #8: [4, 7], #9: [4, 8], #10: [5, 6], #11: [5, 7], #12: [5, 8], #13: [6, 7], #14: [6, 8], #15: [7, 8]

or

#1: [3, 4], #2: [4, 5], #3: [5, 6], #4: [6, 7], #5: [7, 8], #6: [3, 5], #7: [4, 6], #8: [5, 7], #9: [6, 8], #10: [3, 6], #11: [4, 7], #12: [5, 8], #13: [3, 7], #14: [4, 8], #15: [3, 8].

The selected pair index can be derived as: index=((m0*QP+n0)>>00)+((p0*q0)>>r0)+s0  (27)

In the above equation, the QP is the slice QP, the m0, n0, o0, p0, q0, r0, and s0 are the integer values. Note that, if a variable Y is a negative value, the (X>>Y) means (X<<(−Y)). If the derived index is not a integer value, it will be rounded to an integer value.

In one embodiment, the m0, and p0 are stored as the initial values for different contexts while the n0, o0, q0, r0, s0 are fixed values and can be 0.

In the above method, the multiple initial values can be packed into one initial value. For example, in method-2, the m0, p0, m1, p1 can be packed into one initial value.

In the above method, for a context, the initial values can be different in different slice or the same for different slice. For example, one initial value or value set for I-slice, one initial value or value set for P-slice, one initial value or value set for B-slice. in another example, one initial value or value set for I-slice, one initial value or value set for P-slice and B-slice.

RangeLPS Derivation

In CABAC encoder and decoder, a recursive interval-subdividing procedure is performed in binary arithmetic encoding unit 130 and binary arithmetic decoding unit 140. In the interval-subdividing, a value of rangeLPS, rangeOne, or rangeZero is derived. In JCTVC-F254 and VCEG-AZ07, the rangeOne is derived from table look up. The rangeOne table covers the probability from 0.0 to 1.0. However, it makes the LUT too large to be implemented in terms of hardware cost. The LUT is 144 times of the LUT of HEVC. Moreover, because the entry value of the RangeOne or RangeZero is derived from the MinRange (i.e., eq. (17)), the coding efficiency will dropped dramatically if the down-sampled LUT is used.

Therefore, it is proposed to store the probability range from 0.0 to 0.5 only in the present invention. The values in the other half table can be derived by using “range−rangeLPS”. The number of rows defines the resolution of the probabilities. For example, we can design a rangeLPS table with 64 rows for probability range equal to 0.5 to 0.0. Each row represents the rangeLPS for a probability range of 1/64. The value of rangeLPS is derived by (range A)*(Prob B). For example, Table 2 shows a rangeLPS table with 4 columns and 64 rows. The first row represents the rangeLPS for probability within 63/128 to 64/128 in four different range sections. In Table 2, the range A is range Mid and Prob B is Prob Max. The value of rangeLPS is derived by (range Mid)*(Prob Max). In JCTVC-F254 and VCEG-AZ07, for Table 2, if the probability of one is larger than 0.5 (e.g. 0.64), it means that the probability of zero is 0.36. The 0.36 (in 18^(th) row) will be used to find the range for rangeZero. The rangeOne can be derived by (range−rangeZero).

TABLE 2 rangeLPS table for a certain probability with (range Mid) * (Prob Max) (Range>>6)&3 rangeIdx 0 1 2 3 range Min 256 320 384 448 range Max 319 383 447 511 range Mid 288 352 416 480 Prob Max Prob Min probIdx 64/128 63/128 63 144 176 208 240 63/128 62/128 62 142 173 205 236 62/128 61/128 61 140 171 202 233 61/128 60/128 60 137 168 198 229 60/128 59/128 59 135 165 195 225 59/128 58/128 58 133 162 192 221 58/128 57/128 57 131 160 189 218 57/128 56/128 56 128 157 185 214 56/128 55/128 55 126 154 182 210 55/128 54/128 54 124 151 179 206 54/128 53/128 53 122 149 176 203 53/128 52/128 52 119 146 172 199 52/128 51/128 51 117 143 169 195 51/128 50/128 50 115 140 166 191 50/128 49/128 49 113 138 163 188 49/128 48/128 48 110 135 159 184 48/128 47/128 47 108 132 156 180 47/128 46/128 46 106 129 153 176 46/128 45/128 45 104 127 150 173 45/128 44/128 44 101 124 146 169 44/128 43/128 43 99 121 143 165 43/128 42/128 42 97 118 140 161 42/128 41/128 41 95 116 137 158 41/128 40/128 40 92 113 133 154 40/128 39/128 39 90 110 130 150 39/128 38/128 38 88 107 127 146 38/128 37/128 37 86 105 124 143 37/128 36/128 36 83 102 120 139 36/128 35/128 35 81 99 117 135 35/128 34/128 34 79 96 114 131 34/128 33/128 33 77 94 111 128 33/128 32/128 32 74 91 107 124 32/128 31/128 31 72 88 104 120 31/128 30/128 30 70 85 101 116 30/128 29/128 29 68 83 98 113 29/128 28/128 28 65 80 94 109 28/128 27/128 27 63 77 91 105 27/128 26/128 26 61 74 88 101 26/128 25/128 25 59 72 85 98 25/128 24/128 24 56 69 81 94 24/128 23/128 23 54 66 78 90 23/128 22/128 22 52 63 75 86 22/128 21/128 21 50 61 72 83 21/128 20/128 20 47 58 68 79 20/128 19/128 19 45 55 65 75 19/128 18/128 18 43 52 62 71 18/128 17/128 17 41 50 59 68 17/128 16/128 16 38 47 55 64 16/128 15/128 15 36 44 52 60 15/128 14/128 14 34 41 49 56 14/128 13/128 13 32 39 46 53 13/128 12/128 12 29 36 42 49 12/128 11/128 11 27 33 39 45 11/128 10/128 10 25 30 36 41 10/128 09/128 9 23 28 33 38 09/128 08/128 8 20 25 29 34 08/128 07/128 7 18 22 26 30 07/128 06/128 6 16 19 23 26 06/128 05/128 5 14 17 20 23 05/128 04/128 4 11 14 16 19 04/128 03/128 3 9 11 13 15 03/128 02/128 2 7 8 10 11 02/128 01/128 1 5 6 7 8 01/128 00/128 0 2 3 3 4

Table 3 shows another value derivation method that rangeLPS is derived by (range Mid)*(Prob Mid) with a 32×8 table. The column and row index of Table 3 can be (Range>>5)&7 and (Prob>>9) respectively, where the probability is represented by 15-bit values. If the (Prob>>9) is larger than 31, the value of (63−(Prob>>9)) is used to represent the column index (the probIdx) for table look up. For example, if the Prob corresponds to the probability of a bin value equal to one, the probability is represented by a 15-bit value, and if (Prob>>9) is smaller than 32, the (Range>>5)&7 and (Prob>>9) are used for table look up. The derived value is the rangeOne and the rangeZero is derived as (range−rangeOne). If (Prob>>9) is equal to or larger than 32 (i.e., the Prob >16384), the (Range>>5)&7 and (63−(Prob>>9)) (i.e., (32767−P)>>9) are used for table look up. The derived value is the rangeZero and the rangeOne is derived from (range−rangeZero).

TABLE 3 rangeLPS table for a certain probability with (range Mid) * (Prob Mid) (Range>>5)&7 rangeIdx  0   1   2   3   4   5   6   7  range Min 256 288 320 352 384 416 448 480 range Max 287 319 351 383 415 447 479 511 range Mid 272 304 336 368 400 432 464 496 probIdx Prob Max Prob Mid Prob Min (Prob>>9) 32/64 31.5/64 31/64 31 134 150 165 181 197 213 228 244 31/64 30.5/64 30/64 30 130 145 160 175 191 206 221 236 30/64 29.5/64 29/64 29 125 140 155 170 184 199 214 229 29/64 28.5/64 28/64 28 121 135 150 164 178 192 207 221 28/64 27.5/64 27/64 27 117 131 144 158 172 186 199 213 27/64 26.5/64 26/64 26 113 126 139 152 166 179 192 205 26/64 25.5/64 25/64 25 108 121 134 147 159 172 185 198 25/64 24.5/64 24/64 24 104 116 129 141 153 165 178 190 24/64 23.5/64 23/64 23 100 112 123 135 147 159 170 182 23/64 22.5/64 22/64 22 96 107 118 129 141 152 163 174 22/64 21.5/64 21/64 21 91 102 113 124 134 145 156 167 21/64 20.5/64 20/64 20 87 97 108 118 128 138 149 159 20/64 19.5/64 19/64 19 83 93 102 112 122 132 141 151 19/64 18.5/64 18/64 18 79 88 97 106 116 125 134 143 18/64 17.5/64 17/64 17 74 83 92 101 109 118 127 136 17/64 16.5/64 16/64 16 70 78 87 95 103 111 120 128 16/64 15.5/64 15/64 15 66 74 81 89 97 105 112 120 15/64 14.5/64 14/64 14 62 69 76 83 91 98 105 112 14/64 13.5/64 13/64 13 57 64 71 78 84 91 98 105 13/64 12.5/64 12/64 12 53 59 66 72 78 84 91 97 12/64 11.5/64 11/64 11 49 55 60 66 72 78 83 89 11/64 10.5/64 10/64 10 45 50 55 60 66 71 76 81 10/64 09.5/64 09/64 9 40 45 50 55 59 64 69 74 09/64 08.5/64 08/64 8 36 40 45 49 53 57 62 66 08/64 07.5/64 07/64 7 32 36 39 43 47 51 54 58 07/64 06.5/64 06/64 6 28 31 34 37 41 44 47 50 06/64 05.5/64 05/64 5 23 26 29 32 34 37 40 43 05/64 04.5/64 04/64 4 19 21 24 26 28 30 33 35 04/64 03.5/64 03/64 3 15 17 18 20 22 24 25 27 03/64 02.5/64 02/64 2 11 12 13 14 16 17 18 19 02/64 01.5/64 01/64 1 6 7 8 9 9 10 11 12 01/64 00.5/64 00/64 0 2 2 3 3 3 3 4 4

The Table can be also derived by using (range Min)*(Prob Max) as shown in Table 4.

TABLE 4 rangeLPS table for a certain probability with (range Min) * (Prob Max) (Range>>5)&7 rangeIdx  0   1   2   3   4   5   6   7  range Min 256 288 320 352 384 416 448 480 range Max 287 319 351 383 415 447 479 511 range Mid 272 304 336 368 400 432 464 496 probIdx Prob Max Prob Mid Prob Min (Prob>>9) 32/64 31.5/64 31/64 31 128 144 160 176 192 208 224 240 31/64 30.5/64 30/64 30 124 140 155 171 186 202 217 233 30/64 29.5/64 29/64 29 120 135 150 165 180 195 210 225 29/64 28.5/64 28/64 28 116 131 145 160 174 189 203 218 28/64 27.5/64 27/64 27 112 126 140 154 168 182 196 210 27/64 26.5/64 26/64 26 108 122 135 149 162 176 189 203 26/64 25.5/64 25/64 25 104 117 130 143 156 169 182 195 25/64 24.5/64 24/64 24 100 113 125 138 150 163 175 188 24/64 23.5/64 23/64 23 96 108 120 132 144 156 168 180 23/64 22.5/64 22/64 22 92 104 115 127 138 150 161 173 22/64 21.5/64 21/64 21 88 99 110 121 132 143 154 165 21/64 20.5/64 20/64 20 84 95 105 116 126 137 147 158 20/64 19.5/64 19/64 19 80 90 100 110 120 130 140 150 19/64 18.5/64 18/64 18 76 86 95 105 114 124 133 143 18/64 17.5/64 17/64 17 72 81 90 99 108 117 126 135 17/64 16.5/64 16/64 16 68 77 85 94 102 111 119 128 16/64 15.5/64 15/64 15 64 72 80 88 96 104 112 120 15/64 14.5/64 14/64 14 60 68 75 83 90 98 105 113 14/64 13.5/64 13/64 13 56 63 70 77 84 91 98 105 13/64 12.5/64 12/64 12 52 59 65 72 78 85 91 98 12/64 11.5/64 11/64 11 48 54 60 66 72 78 84 90 11/64 10.5/64 10/64 10 44 50 55 61 66 72 77 83 10/64 09.5/64 09/64 9 40 45 50 55 60 65 70 75 09/64 08.5/64 08/64 8 36 41 45 50 54 59 63 68 08/64 07.5/64 07/64 7 32 36 40 44 48 52 56 60 07/64 06.5/64 06/64 6 28 32 35 39 42 46 49 53 06/64 05.5/64 05/64 5 24 27 30 33 36 39 42 45 05/64 04.5/64 04/64 4 20 23 25 28 30 33 35 38 04/64 03.5/64 03/64 3 16 18 20 22 24 26 28 30 03/64 02.5/64 02/64 2 12 14 15 17 18 20 21 23 02/64 01.5/64 01/64 1 8 9 10 11 12 13 14 15 01/64 00.5/64 00/64 0 4 5 5 6 6 7 7 8

In one embodiment to derive the RangeOne (or RangeZero), for a k-bit probability (2^(k)>P>0) and a 9-bits range, the probLPS can be calculated according to probLPS=(P>=2^(k−1)) ? 2^(k)−1−P: P. The probIdx can be derived as probLPS >>(k−n−1), where the rangeLPS table has 2^(n) rows. The rangeIdx is derived as (range>>(8−m))−(256>>m), ((range−256)>>(8−m)), or (range>>(8−m))&(2^(m)−1), where the rangeLPS table has 2^(m) columns. The rangeLPS can be calculated according to rangeLPS=rangeLPSTable[probIdx][rangeIdx]. If P is equal to or larger than 2^(k−1) (i.e., the k-th bit of P equal to 1), the rangeOne and rangeZero can be calculated according to rangeOne=range−rangeLPS and rangeZero=rangeLPS respectively. Otherwise (i.e., P smaller than 2^(k−1)), the rangeOne and rangeZero can be calculated according to rangeOne=rangeLPS and rangeZero=range−rangeLPS respectively.

In the example of JCTVC-F254 and VCEG-AZ07, k is 15, the probLPS, probIdx and rangeIdx can be calculated according to probLPS=(P>=16384) ? 32767−P: P, probIdx=probLPS>>8, and rangeIdx=(range>>6)&3 respectively. If P is equal to or larger than 16384, the rangeOne and rangeZero can be calculated according to rangeOne=range−rangeLPS and rangeZero=rangeLPS respectively. Otherwise (i.e., P smaller than 16384), the rangeOne and rangeZero can be calculated according to rangeOne=rangeLPS and rangeZero=range−rangeLPS respectively.

The rangeLPS value can be derived by calculating (range Min)*(Prob Max), (range Min)*(Prob Mid), (range Min)*(Prob Min), (range Mid)*(Prob Max), (range Mid)*(Prob Mid), (range Mid)*(Prob Min), (range Max)*(Prob Max), (range Max)*(Prob Mid), or (range Max)*(Prob Min). The entire values in the rangeLPS table can be derived by using multiplier.

For example, if the rangeLPS table is derived by using (range Min)*(Prob Max), the entry value can be derived by using a formula. For example, for a k-bit probability (2^(k)>P>0) with a 9-bits range, the probLPS can be calculated according to probLPS=(P>=2^(k−1)) ? 2^(k)−1−P: P. The probIdx can be derived as probLPS >>(k−n−1). The rangeIdx is derived as (range>>(8−m)). The rangeLPS can be calculated according to rangeLPS=((probIdx+1)*rangeIdx)>>(k−n−m−6), ((probIdx)*rangeIdx+rangeIdx)>>(k−n−m−6), (((probIdx)*rangeIdx)>>(k−n−m−6))+((rangeIdx)>>(k−n−m−6)), or (((probIdx+offset1)*rangeIdx+offset2)>>(k−n−m−6))+offset3, where the offset1, offset2, and offset3 are integers. For example, the offset1 and the offset2 can be 0, the offset3 can be 2, 3, or 4.

In one example, k is 15 and if the n is 5 and m is 3, the probLPS, probIdx and rangeIdx can be calculated according to probLPS=(P>=16384) ? 32767−P: P, probIdx=probLPS>>9, and rangeIdx=(range>>5) respectively. The rangeLPS can be calculated according to rangeLPS=((probIdx+1)*rangeIdx)>>1, or ((probIdx*rangeIdx)>>1)+(rangeIdx>>1), or ((probIdx*rangeIdx)>>1)+4. If P is equal to or larger than 16384, the rangeOne and rangeZero can be calculated according to rangeOne=range−rangeLPS and rangeZero=rangeLPS respectively. Otherwise (i.e., is smaller than 16384), the rangeOne and rangeZero can be calculated according to rangeOne=rangeLPS and rangeZero=range−rangeLPS respectively.

The value of rangeLPS can be pre-calculated and stored in a look-up table. For example, Table 4 is the result of “rangeLPS=((probIdx+1)*rangeIdx)>>1” by using probIdx and rangeIdx for table look-up. Table 5 is the result of “rangeLPS=((probIdx*rangeIdx)>>1)+(rangeIdx>>1)” by using probIdx and rangeIdx for table look-up.

TABLE 5 rangeLPS table for a certain probability with (range Min) * (Prob Max) (Range>>5)&7 rangeIdx  0   1   2   3   4   5   6   7  range Min 256 288 320 352 384 416 448 480 range Max 287 319 351 383 415 447 479 511 range Mid 272 304 336 368 400 432 464 496 probIdx Prob Max Prob Mid Prob Min (Prob>>9) 32/64 31.5/64 31/64 31 128 145 160 177 192 209 224 241 31/64 30.5/64 30/64 30 124 140 155 171 186 202 217 233 30/64 29.5/64 29/64 29 120 136 150 166 180 196 210 226 29/64 28.5/64 28/64 28 116 131 145 160 174 189 203 218 28/64 27.5/64 27/64 27 112 127 140 155 168 183 196 211 27/64 26.5/64 26/64 26 108 122 135 149 162 176 189 203 26/64 25.5/64 25/64 25 104 118 130 144 156 170 182 196 25/64 24.5/64 24/64 24 100 113 125 138 150 163 175 188 24/64 23.5/64 23/64 23 96 109 120 133 144 157 168 181 23/64 22.5/64 22/64 22 92 104 115 127 138 150 161 173 22/64 21.5/64 21/64 21 88 100 110 122 132 144 154 166 21/64 20.5/64 20/64 20 84 95 105 116 126 137 147 158 20/64 19.5/64 19/64 19 80 91 100 111 120 131 140 151 19/64 18.5/64 18/64 18 76 86 95 105 114 124 133 143 18/64 17.5/64 17/64 17 72 82 90 100 108 118 126 136 17/64 16.5/64 16/64 16 68 77 85 94 102 111 119 128 16/64 15.5/64 15/64 15 64 73 80 89 96 105 112 121 15/64 14.5/64 14/64 14 60 68 75 83 90 98 105 113 14/64 13.5/64 13/64 13 56 64 70 78 84 92 98 106 13/64 12.5/64 12/64 12 52 59 65 72 78 85 91 98 12/64 11.5/64 11/64 11 48 55 60 67 72 79 84 91 11/64 10.5/64 10/64 10 44 50 55 61 66 72 77 83 10/64 09.5/64 09/64 9 40 46 50 56 60 66 70 76 09/64 08.5/64 08/64 8 36 41 45 50 54 59 63 68 08/64 07.5/64 07/64 7 32 37 40 45 48 53 56 61 07/64 06.5/64 06/64 6 28 32 35 39 42 46 49 53 06/64 05.5/64 05/64 5 24 28 30 34 36 40 42 46 05/64 04.5/64 04/64 4 20 23 25 28 30 33 35 38 04/64 03.5/64 03/64 3 16 19 20 23 24 27 28 31 03/64 02.5/64 02/64 2 12 14 15 17 18 20 21 23 02/64 01.5/64 01/64 1 8 10 10 12 12 14 14 16 01/64 00.5/64 00/64 0 4 5 5 6 6 7 7 8

In another embodiment, if the rangeLPS table is derived by using (range Min)*(Prob Max), the entry value can be derived by using a formula. For example, for a k-bit probability (2^(k)>P>0) and a 9-bits range, the probIdx can be calculated according to probIdx=>=2^(k−1)) ? 2^(n+1) (P>>(k−n−1)): (P>>(k−n−1))+1. The rangeIdx is derived as (range>>(8−m)). The rangeLPS=(probIdx*rangeIdx)>>(k−n−m−6).

In the example of JCTVC-F254 and VCEG-AZ07, k is 15 and if the n is 5 and m is 3, the probIdx and rangeIdx can be calculated according to probIdx=(P>=16384) ? 64−(P>>9): (P>>9)+1 and rangeIdx=(range>>5) respectively. The rangeLPS can be calculated according to rangeLPS=(probIdx*rangeIdx)>>1. If P is equal to or larger than 16384, the rangeOne and rangeZero can be calculated according to rangeOne=range−rangeLPS and rangeZero=rangeLPS respectively. Otherwise (P is smaller than 16384), the rangeOne and rangeZero can be calculated according to rangeOne=rangeLPS and rangeZero=range−rangeLPS respectively.

In another embodiment, if the rangeLPS table can be derived by using a formula. For example, for a k-bit probability (2^(k)>P>0) and a 9-bits range, the probIdx can be calculated according to probIdx=>=2^(k−1)) ? 2^(n+1)−(P>>(k−n−1)): max(1,(P>>(k−n−1))), or probIdx=>=2^(k−1)) ? 2^(n+1)−(P>>(k−n−1))−1: max(1,(P>>(k−n−1))), where the rangeLPS table has 2^(n) rows. The rangeIdx is derived as (range>>(8−m)), where the rangeLPS table has 2^(m) columns. The rangeLPS can be calculated according to rangeLPS=(probIdx*rangeIdx)>>(k−n−m−6), where k can be 15, n can be 5, and m can be 3.

In another embodiment, if the rangeLPS table is derived by using (range mid)*(Prob Max), the entry value can be derived by using a formula. For example, for a k-bit probability (2^(k)>P>0) and a 9-bits range, the probIdx can be calculated according to probIdx=>=2^(k−1)) ? 2^(n+1)−(P>>(k−n−1)): (P>>(k−n−1))+1. The rangeIdx is derived as 2*(range>>(8−m))+1. The rangeLPS can be calculated according to rangeLPS=(probIdx*rangeIdx)>>(k−n−m−6+1), where k can be 15, n can be 5, and m can be 3.

In another embodiment, if the rangeLPS table is derived by using (range min)*(Prob mid), the entry value can be derived by using a formula. For example, for a k-bit probability (2^(k)>P>0) and a 9-bits range, the probIdx′ can be calculated according to probIdx′=>=2 ^(k−1)) ? 2^(n+1)−(P>>(k−n−1))−1: (P>>(k−n−1)). The probIdx is calculated according to probIdx=2*probIdx′+1. The rangeIdx is derived as (range>>(8−m)). The rangeLPS can be calculated according to rangeLPS=(probIdx*rangeIdx)>>(k−n−m−6+1), where k can be 15, n can be 5, and m can be 3. We can use an 8-bits*(1<<m)*(1<<n) table to store the pre-calculated rangeLPS value. For example, if n is 5 and m is 4, in Table 6, a 8-bits*16*32 table can be used to derive the rangeLPS value by using probIdx′ and (range>>(8−m))&((1<<m)−1). For example, if n is 5 and m is 3, in Table 7, an 8-bits*8*32 table can be used to derive the rangeLPS value by using probIdx′ and (range>>(8−m))& ((1<<m)−1).

TABLE 6 rangeLPS table for a certain probability with (range min) * (Prob Mid) (Range>>4)&15 rangeIdx 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 range Min 256 272 288 304 320 336 352 368 384 400 416 432 448 464 480 496 range Max 271 287 303 319 335 351 367 383 399 415 431 447 463 479 495 511 range Mid 264 280 296 312 328 344 360 376 392 408 424 440 456 472 488 504 probIdx′ Prob Mid (Prob>>9) 31.5/64 31 126 133 141 149 157 165 173 181 189 196 204 212 220 228 236 244 30.5/64 30 122 129 137 144 152 160 167 175 183 190 198 205 213 221 228 236 29.5/64 29 118 125 132 140 147 154 162 169 177 184 191 199 206 213 221 228 28.5/64 28 114 121 128 135 142 149 156 163 171 178 185 192 199 206 213 220 27.5/64 27 110 116 123 130 137 144 151 158 165 171 178 185 192 199 206 213 26.5/64 26 106 112 119 125 132 139 145 152 159 165 172 178 185 192 198 205 25.5/64 25 102 108 114 121 127 133 140 146 153 159 165 172 178 184 191 197 24.5/64 24 98 104 110 116 122 128 134 140 147 153 159 165 171 177 183 189 23.5/64 23 94 99 105 111 117 123 129 135 141 146 152 158 164 170 176 182 22.5/64 22 90 95 101 106 112 118 123 129 135 140 146 151 157 163 168 174 21.5/64 21 86 91 96 102 107 112 118 123 129 134 139 145 150 155 161 166 20.5/64 20 82 87 92 97 102 107 112 117 123 128 133 138 143 148 153 158 19.5/64 19 78 82 87 92 97 102 107 112 117 121 126 131 136 141 146 151 18.5/64 18 74 78 83 87 92 97 101 106 111 115 120 124 129 134 138 143 17.5/64 17 70 74 78 83 87 91 96 100 105 109 113 118 122 126 131 135 16.5/64 16 66 70 74 78 82 86 90 94 99 103 107 111 115 119 123 127 15.5/64 15 62 65 69 73 77 81 85 89 93 96 100 104 108 112 116 120 14.5/64 14 58 61 65 68 72 76 79 83 87 90 94 97 101 105 108 112 13.5/64 13 54 57 60 64 67 70 74 77 81 84 87 91 94 97 101 104 12.5/64 12 50 53 56 59 62 65 68 71 75 78 81 84 87 90 93 96 11.5/64 11 46 48 51 54 57 60 63 66 69 71 74 77 80 83 86 89 10.5/64 10 42 44 47 49 52 55 57 60 63 65 68 70 73 76 78 81 09.5/64 9 38 40 42 45 47 49 52 54 57 59 61 64 66 68 71 73 08.5/64 8 34 36 38 40 42 44 46 48 51 53 55 57 59 61 63 65 07.5/64 7 30 31 33 35 37 39 41 43 45 46 48 50 52 54 56 58 06.5/64 6 26 27 29 30 32 34 35 37 39 40 42 43 45 47 48 50 05.5/64 5 22 23 24 26 27 28 30 31 33 34 35 37 38 39 41 42 04.5/64 4 18 19 20 21 22 23 24 25 27 28 29 30 31 32 33 34 03.5/64 3 14 14 15 16 17 18 19 20 21 21 22 23 24 25 26 27 02.5/64 2 10 10 11 11 12 13 13 14 15 15 16 16 17 18 18 19 01.5/64 1 6 6 6 7 7 7 8 8 9 9 9 10 10 10 11 11 00.5/64 0 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3

TABLE 7 rangeLPS table for a certain probability with (range min) * (Prob Mid) (Range>>5)&7 rangeIdx  0   1   2   3   4   5   6   7  range Min 256 288 320 352 384 416 448 480 range Max 287 319 351 383 415 447 479 511 range Mid 272 304 336 368 400 432 464 496 probIdx′ Prob Max Prob Mid Prob Min (Prob>>9) 32/64 31.5/64 31/64 31 126 141 157 173 189 204 220 236 31/64 30.5/64 30/64 30 122 137 152 167 183 198 213 228 30/64 29.5/64 29/64 29 118 132 147 162 177 191 206 221 29/64 28.5/64 28/64 28 114 128 142 156 171 185 199 213 28/64 27.5/64 27/64 27 110 123 137 151 165 178 192 206 27/64 26.5/64 26/64 26 106 119 132 145 159 172 185 198 26/64 25.5/64 25/64 25 102 114 127 140 153 165 178 191 25/64 24.5/64 24/64 24 98 110 122 134 147 159 171 183 24/64 23.5/64 23/64 23 94 105 117 129 141 152 164 176 23/64 22.5/64 22/64 22 90 101 112 123 135 146 157 168 22/64 21.5/64 21/64 21 86 96 107 118 129 139 150 161 21/64 20.5/64 20/64 20 82 92 102 112 123 133 143 153 20/64 19.5/64 19/64 19 78 87 97 107 117 126 136 146 19/64 18.5/64 18/64 18 74 83 92 101 111 120 129 138 18/64 17.5/64 17/64 17 70 78 87 96 105 113 122 131 17/64 16.5/64 16/64 16 66 74 82 90 99 107 115 123 16/64 15.5/64 15/64 15 62 69 77 85 93 100 108 116 15/64 14.5/64 14/64 14 58 65 72 79 87 94 101 108 14/64 13.5/64 13/64 13 54 60 67 74 81 87 94 101 13/64 12.5/64 12/64 12 50 56 62 68 75 81 87 93 12/64 11.5/64 11/64 11 46 51 57 63 69 74 80 86 11/64 10.5/64 10/64 10 42 47 52 57 63 68 73 78 10/64 09.5/64 09/64 9 38 42 47 52 57 61 66 71 09/64 08.5/64 08/64 8 34 38 42 46 51 55 59 63 08/64 07.5/64 07/64 7 30 33 37 41 45 48 52 56 07/64 06.5/64 06/64 6 26 29 32 35 39 42 45 48 06/64 05.5/64 05/64 5 22 24 27 30 33 35 38 41 05/64 04.5/64 04/64 4 18 20 22 24 27 29 31 33 04/64 03.5/64 03/64 3 14 15 17 19 21 22 24 26 03/64 02.5/64 02/64 2 10 11 12 13 15 16 17 18 02/64 01.5/64 01/64 1 6 6 7 8 9 9 10 11 01/64 00.5/64 00/64 0 2 2 2 2 3 3 3 3

In another embodiment, if the rangeLPS table is derived by using (range mid)*(Prob mid), the entry value can be derived by using a formula. For example, for a k-bit probability (2^(k)>P>0) and a 9-bits range, the probIdx′ can be calculated according to probIdx′=>=2^(k−1)) ? 2^(n+1)−(P>>(k−n−1))−1: (P>>(k−n−1)), or probIdx′=>=2 ^(k−1)) ? (2^(k)−P−1)>>(k−n−1): (P>>(k−n−1)). The probIdx is calculated according to probIdx=2*probIdx′+1. The rangeIdx is derived as 2*(range>>(8−m))+1. The rangeLPS can be calculated according to rangeLPS=(probIdx*rangeIdx)>>(k−n−m−6+2), k can be 15, n can be 5, and m can be 3. For example, the probIdx′ can be calculated according to probIdx′=(P>=16384) ? (32767−P)>>9: P>>9, or probIdx′=(P>=16384) ? 63−(P>>9): (P>>9). The probIdx is calculated according to probIdx=2*probIdx′+1. The rangeIdx is derived as 2*(range>>5)+1. The rangeLPS can be calculated according to rangeLPS=(probIdx*rangeIdx)>>3. We can use an 8-bits*(1<<m)*(1<<n) table to store the pre-calculated rangeLPS value. For example, if n is 5 and m is 3, in Table 8, an 8-bits*8*32 table can be used to derive the rangeLPS value by using probIdx′ and (range>>(8−m))&((1<<m)−1). For example to derive the RangeOne (or RangeZero), the probIdx′ can be calculated according to probIdx′=(P>=2^(k−1)) ? (2^(k)−1−P)>>(k−n−1): P>>(k−n−1), or probIdx′=>=2^(k−1)) ? 2^(n+1)(P>>(k−n−1))−1: (P>>(k−n−1)). The rangeIdx′ is derived as (range>>(8−m))−(256>>m), ((range−256)>>(8−m)), or (range>>(8−m))&(2^(m)−1). The rangeLPS can be calculated according to rangeLPS=rangeLPSTable[probIdx′][rangeIdx′]. If P is equal to or larger than 2^(k−1) (i.e., the k-th bit of P equal to 1), the rangeOne and rangeZero can be calculated according to rangeOne=range−rangeLPS and rangeZero=rangeLPS respectively. Otherwise (i.e., P smaller than 2^(k−1)), the rangeOne and rangeZero can be calculated according to rangeOne=rangeLPS and rangeZero=range−rangeLPS respectively. For example, if k is 15 and if then is 5 and m is 3, the probIdx′ can be calculated according to probIdx′=(P>=16384) ? (32767−P)>>9: P>>9, or probIdx′=(P>=16384) ? 63−(P>>9): (P>>9). The rangeIdx′ is derived as (range>>5)&7. The rangeLPS can be calculated according to rangeLPS=rangeLPSTable[probIdx′][rangeIdx′]. If P is equal to or larger than 16384, the rangeOne and rangeZero can be calculated according to rangeOne=range−rangeLPS and rangeZero=rangeLPS respectively. Otherwise (i.e., P smaller than 16384), the rangeOne and rangeZero can be calculated according to rangeOne=rangeLPS and rangeZero=range−rangeLPS.

TABLE 8 rangeLPS table for a certain probability with (range Mid) * (Prob Mid) (Range>>5)&7 rangeIdx  0   1   2   3   4   5   6   7  range Min 256 288 320 352 384 416 448 480 range Max 287 319 351 383 415 447 479 511 range Mid 272 304 336 368 400 432 464 496 probIdx′ Prob Max Prob Mid Prob Min (Prob>>9) 32/64 31.5/64 31/64 31 133 149 165 181 196 212 228 244 31/64 30.5/64 30/64 30 129 144 160 175 190 205 221 236 30/64 29.5/64 29/64 29 125 140 154 169 184 199 213 228 29/64 28.5/64 28/64 28 121 135 149 163 178 192 206 220 28/64 27.5/64 27/64 27 116 130 144 158 171 185 199 213 27/64 26.5/64 26/64 26 112 125 139 152 165 178 192 205 26/64 25.5/64 25/64 25 108 121 133 146 159 172 184 197 25/64 24.5/64 24/64 24 104 116 128 140 153 165 177 189 24/64 23.5/64 23/64 23 99 111 123 135 146 158 170 182 23/64 22.5/64 22/64 22 95 106 118 129 140 151 163 174 22/64 21.5/64 21/64 21 91 102 112 123 134 145 155 166 21/64 20.5/64 20/64 20 87 97 107 117 128 138 148 158 20/64 19.5/64 19/64 19 82 92 102 112 121 131 141 151 19/64 18.5/64 18/64 18 78 87 97 106 115 124 134 143 18/64 17.5/64 17/64 17 74 83 91 100 109 118 126 135 17/64 16.5/64 16/64 16 70 78 86 94 103 111 119 127 16/64 15.5/64 15/64 15 65 73 81 89 96 104 112 120 15/64 14.5/64 14/64 14 61 68 76 83 90 97 105 112 14/64 13.5/64 13/64 13 57 64 70 77 84 91 97 104 13/64 12.5/64 12/64 12 53 59 65 71 78 84 90 96 12/64 11.5/64 11/64 11 48 54 60 66 71 77 83 89 11/64 10.5/64 10/64 10 44 49 55 60 65 70 76 81 10/64 09.5/64 09/64 9 40 45 49 54 59 64 68 73 09/64 08.5/64 08/64 8 36 40 44 48 53 57 61 65 08/64 07.5/64 07/64 7 31 35 39 43 46 50 54 58 07/64 06.5/64 06/64 6 27 30 34 37 40 43 47 50 06/64 05.5/64 05/64 5 23 26 28 31 34 37 39 42 05/64 04.5/64 04/64 4 19 21 23 25 28 30 32 34 04/64 03.5/64 03/64 3 14 16 18 20 21 23 25 27 03/64 02.5/64 02/64 2 10 11 13 14 15 16 18 19 02/64 01.5/64 01/64 1 6 7 7 8 9 10 10 11 01/64 00.5/64 00/64 0 2 2 2 2 3 3 3 3

The general form, for a k-bit probability (2^(k)>P>0) and a 9-bits range, the probIdx′ can be calculated according to probIdx′=>=2^(k−1)) ? 2^(n+1)(P>>(k−n−1))−1: (P>>(k−n−1)). The probIdx is calculated according to probIdx=a*probIdx′+b. The rangeIdx is derived as c*(range>>(8−m))+d. The rangeLPS can be calculated according to rangeLPS=((probIdx*rangeIdx+e)>>(k−n−m−6))/a/c+f There a, b, c, d, e, f are predefined integer values or derived values, k can be 15, n can be 5, and m can be 3.

For the above general form, if the f is zero (i.e., no offset is added), some methods are proposed to prevent the value of the derived rangeLPS to be too small. In one method, the clip is used. If the rangeLPS is smaller than a threshold, the rangeLPS value is set as the threshold. The threshold can be 2, 3, or 4. In another method, the rangeLPS is “bit-wise or” with a value. The value can be 2, 3, or 4. For example, the rangeLPS=(rangeLPS value), or rangeLPS=(rangeLPS OR value).

For example, the a and c are equal to 1, b, c, d, and e are equal to 0, f is equal to 4. If 16-bit probability (2¹⁶>P>0) and a 9-bits range is used, n is 5, m is 3, the probIdx=(P>=16384) ? 63−(P>>9): (P>>9). The rangeIdx is derived as (range>>5). The rangeLPS=((probIdx*rangeIdx)>>1)+4. We can use an 8-bits*(1<<m)*(1<<n) table to store the pre-calculated rangeLPS value. For example, if n is 5 and m is 3, in Table 9, an 8-bits*8*32 table can be used to derive the rangeLPS value.

In another example, if 16-bit probability (2¹⁶>P>0) and a 9-bits range is used, n is 5, m is 3, the probIdx=(P>=16384) ? 63−(P>>9): (P>>9). The rangeIdx is derived as (range>>5). The rangeLPS=((probIdx*rangeIdx)>>1)|4. In another example, if ((probIdx*rangeIdx)>>1)<4, rangeLPS is set equal to 4. Otherwise, the rangeLPS is set equal to ((probIdx*rangeIdx)>>1).

TABLE 9 rangeLPS table for a certain probability with ((probIdx * rangeIdx)>>1) + 4 (Range>>5)&7 rangeIdx  0   1   2   3   4   5   6   7  range Min 256 288 320 352 384 416 448 480 range Max 287 319 351 383 415 447 479 511 range Mid 272 304 336 368 400 432 464 496 probIdx′ Prob Max Prob Mid Prob Min (Prob>>9) 32/64 31.5/64 31/64 31 128 143 159 174 190 205 221 236 31/64 30.5/64 30/64 30 124 139 154 169 184 199 214 229 30/64 29.5/64 29/64 29 120 134 149 163 178 192 207 221 29/64 28.5/64 28/64 28 116 130 144 158 172 186 200 214 28/64 27.5/64 27/64 27 112 125 139 152 166 179 193 206 27/64 26.5/64 26/64 26 108 121 134 147 160 173 186 199 26/64 25.5/64 25/64 25 104 116 129 141 154 166 179 191 25/64 24.5/64 24/64 24 100 112 124 136 148 160 172 184 24/64 23.5/64 23/64 23 96 107 119 130 142 153 165 176 23/64 22.5/64 22/64 22 92 103 114 125 136 147 158 169 22/64 21.5/64 21/64 21 88 98 109 119 130 140 151 161 21/64 20.5/64 20/64 20 84 94 104 114 124 134 144 154 20/64 19.5/64 19/64 19 80 89 99 108 118 127 137 146 19/64 18.5/64 18/64 18 76 85 94 103 112 121 130 139 18/64 17.5/64 17/64 17 72 80 89 97 106 114 123 131 17/64 16.5/64 16/64 16 68 76 84 92 100 108 116 124 16/64 15.5/64 15/64 15 64 71 79 86 94 101 109 116 15/64 14.5/64 14/64 14 60 67 74 81 88 95 102 109 14/64 13.5/64 13/64 13 56 62 69 75 82 88 95 101 13/64 12.5/64 12/64 12 52 58 64 70 76 82 88 94 12/64 11.5/64 11/64 11 48 53 59 64 70 75 81 86 11/64 10.5/64 10/64 10 44 49 54 59 64 69 74 79 10/64 09.5/64 09/64 9 40 44 49 53 58 62 67 71 09/64 08.5/64 08/64 8 36 40 44 48 52 56 60 64 08/64 07.5/64 07/64 7 32 35 39 42 46 49 53 56 07/64 06.5/64 06/64 6 28 31 34 37 40 43 46 49 06/64 05.5/64 05/64 5 24 26 29 31 34 36 39 41 05/64 04.5/64 04/64 4 20 22 24 26 28 30 32 34 04/64 03.5/64 03/64 3 16 17 19 20 22 23 25 26 03/64 02.5/64 02/64 2 12 13 14 15 16 17 18 19 02/64 01.5/64 01/64 1 8 8 9 9 10 10 11 11 01/64 00.5/64 00/64 0 4 4 4 4 4 4 4 4

For the derived rangeLPS, it's value can be clipped within a threshold. The threshold can be a fixed value, a predefined value, a signalled value (signalled in sequence/picture/slice/tile-level), or an adaptive value that corresponds to the current range (or range index) or the current probability (or probability index, LPS probability, LPS probability index). In one example, the threshold equal to minimum range in this range index −128 or minimum range in this range index −2q−2, where the q is the bits used for the current range. For example, if a 9-bits range is used and the rangeIdx is derived as (range>>5), the minimum range in this rangeIdx is equal to (rangeIdx<<5). The threshold is equal to (rangeIdx<<5)−128. If the rangeLPS is larger than this threshold, the rangeLPS is set equal to the threshold; otherwise, the rangeLPS is not changed. Table 10 shows the modified Table 8 that the maximum reangeLPS constraint is considered. In another example, the threshold equal to current range −128 or current range −2q−2, where the q is the bits used for the current range. For example, if a 9-bits range is used, the threshold is equal to range −128. If the rangeLPS is larger than this threshold, the rangeLPS is set equal to the threshold; otherwise, the rangeLPS is not changed.

TABLE 10 rangeLPS table for a certain probability with (range Mid) * (Prob Mid) (Range>>5)&7 rangeIdx  0   1   2   3   4   5   6   7  range Min 256 288 320 352 384 416 448 480 range Max 287 319 351 383 415 447 479 511 range Mid 272 304 336 368 400 432 464 496 probIdx′ Prob Max Prob Mid Prob Min (Prob>>9) 32/64 31.5/64 31/64 31 128 149 165 181 196 212 228 244 31/64 30.5/64 30/64 30 128 144 160 175 190 205 221 236 30/64 29.5/64 29/64 29 125 140 154 169 184 199 213 228 29/64 28.5/64 28/64 28 121 135 149 163 178 192 206 220 28/64 27.5/64 27/64 27 116 130 144 158 171 185 199 213 27/64 26.5/64 26/64 26 112 125 139 152 165 178 192 205 26/64 25.5/64 25/64 25 108 121 133 146 159 172 184 197 25/64 24.5/64 24/64 24 104 116 128 140 153 165 177 189 24/64 23.5/64 23/64 23 99 111 123 135 146 158 170 182 23/64 22.5/64 22/64 22 95 106 118 129 140 151 163 174 22/64 21.5/64 21/64 21 91 102 112 123 134 145 155 166 21/64 20.5/64 20/64 20 87 97 107 117 128 138 148 158 20/64 19.5/64 19/64 19 82 92 102 112 121 131 141 151 19/64 18.5/64 18/64 18 78 87 97 106 115 124 134 143 18/64 17.5/64 17/64 17 74 83 91 100 109 118 126 135 17/64 16.5/64 16/64 16 70 78 86 94 103 111 119 127 16/64 15.5/64 15/64 15 65 73 81 89 96 104 112 120 15/64 14.5/64 14/64 14 61 68 76 83 90 97 105 112 14/64 13.5/64 13/64 13 57 64 70 77 84 91 97 104 13/64 12.5/64 12/64 12 53 59 65 71 78 84 90 96 12/64 11.5/64 11/64 11 48 54 60 66 71 77 83 89 11/64 10.5/64 10/64 10 44 49 55 60 65 70 76 81 10/64 09.5/64 09/64 9 40 45 49 54 59 64 68 73 09/64 08.5/64 08/64 8 36 40 44 48 53 57 61 65 08/64 07.5/64 07/64 7 31 35 39 43 46 50 54 58 07/64 06.5/64 06/64 6 27 30 34 37 40 43 47 50 06/64 05.5/64 05/64 5 23 26 28 31 34 37 39 42 05/64 04.5/64 04/64 4 19 21 23 25 28 30 32 34 04/64 03.5/64 03/64 3 14 16 18 20 21 23 25 27 03/64 02.5/64 02/64 2 10 11 13 14 15 16 18 19 02/64 01.5/64 01/64 1 6 7 7 8 9 10 10 11 01/64 00.5/64 00/64 0 2 2 2 2 3 3 3 3

Note that, since the 2^(k)−1 is all ones in binary representation, so the 2^(k)−1−P is just to do the bitwise inverse for k−1 bits of LSB (less significant bit). In hardware implementation, we can do bitwise exclusive or (XOR) for the k-th bit of P and the 1 to k−1-th bits of P to derive the probLPS or probIdx.

In the foregoing embodiments, the size of rangeLPS table can be reduced significantly. Compared with the look up table used in JCTVC-F254 and VCEG-AZ07, the present application can use a smaller look up table, the size is 1/72, 1/144, or 1/288 of the look up table size used in JCTVC-F254 and VCEG-AZ07. Besides, the entire values in the rangeLPS table can be derived by using multiplier, which is easy to implement by using a hardware description language such as Verilog. The value derived from look up table is the same as the value derived by using multiplier. The designer can select the suitable implementation method for deriving the rangeLPS, rangeOne, or rangeZero. The present application provides the design flexibility for implementation.

MV Storage Precision

In HEVC, the MV precision is quarter-pel resolution. The MV is stored in a 16-bits buffer, which defines the MV range that is in −2¹⁵ to 2¹⁵−1. The effective MV range is in [−8192.00, 8191.75] (unit is pixel).

In the next generation video coding, higher MV precision is preferred. The MV precision can be ⅛-pel, 1/16-pel, or finer. If the MV bit-width is fixed or the MV buffer size is fixed, there are two methods to store the MVs in different MV precisions.

A. Store all MV in Highest Precision

If a system has different MV resolution, it stores all MVs in the highest precision.

The low precision MV is left-shifted and clipped to become a high precision MV. The clipping is to limit the maximum effective MV range. For example, if the MV bit-width is 16 bits and the precision is 1/16-pel, the effective MV range is in [−2048.00, 2047.09375] (unit in pixel). The lower precision MV is left-shifted to the same precision, clipped in the range of [−2048.00, 2047.09375] and stored. In another embodiment, the lower precision MV is clipped in the range of [−2048.00, 2047.09375] in low precision and then left-shifted to high precision.

B. Store all MV in Low Precision

If a system has different MV resolution, it stores all MVs in the low precision for MV referencing. But in intermediate process, e.g. motion compensation, affine MV derivation, the high precision MV is used for the process. After the process, the MV is stored in low precision.

C. Store MV in Different Precision

For each MV, a MV resolution index is used to represent the MV precision of the MV. Different MV resolution can have different effective MV range.

D. Method A/C with Low MV Precision for Temporal Collocated MV

In this embodiment, the method A and/or C can be used for storing the MV in current picture. However, the MV is stored in low precision in a MV buffer which is used for temporal collocated MV referencing.

MVP Derivation

In JVET-J0058 (Ye et al., “Merge mode modification on top of Tencent's software in response to CfP”, Joint Video Experts Team (JVET) of ITU-T SG 16 WP 3 and ISO/IEC JTC 1/SC 29/WG 11, 10th Meeting: San Diego, US, 10-20 Apr. 2018, Document: JVET-J0058), a modified merge candidate derivation method is disclosed. Not only the neighbouring 4×4 MVs are used for merge candidate list derivation, but also the 4×4 MVs within left 96 pixels and above 96 pixels range are used for merge candidate list derivation, as illustrated in FIG. 3. In FIG. 3, neighbouring block E is located at the upper-left corner of the current block 310, neighbouring blocks B and C are located at the upper and upper-right locations of the current block 310, and neighbouring blocks A and D are located at the left and lower-left locations of the current block 310. According to JVET-J0058, additional merge candidates are used by extending blocks B and C vertically 320, blocks A and D horizontally 320 and block E diagonally 340 at the block grid having a grid size same as the current block size. Therefore, a lot of MVs are required to store in the memory for merge candidate list derivation.

In this invention, we propose to access the coded MV information in different CUs, as shown in FIG. 4. According to the present invention, the grid for locating extended neighbouring blocks is based on the size of the block containing the neighbouring block. For example, neighbouring block C is contained in coding block 420 and the neighbouring block C1 is used for extended merge candidate. Furthermore, block C1 is contained in coding block 422 and the neighbouring block C2 is used for extended merge candidate. For neighbouring blocks D and B, both are contained in coding block 430 and blocks D1 and B1 are used as extended merge candidate. Furthermore, neighbouring blocks D1 and B1 are contained in coding block 432 and blocks D2 and B2 are used as extended merge candidate. For neighbouring block E, the block is contained in coding block 440 and block E1 above block 440 is used as extended merge candidate. Furthermore, neighbouring blocks E1 are contained in coding block 442 and block E2 is used as extended merge candidate. Compared with the method proposed in JVET-J0058, the position of the accessed block is not a fixed position. It depends on the coded CU size. For example, in the above figure, the distance of B, B′, and B′ blocks are the same, which equal to the CU height. In the below figure, the B, B1, and B2 depends on the CU height of the CUs contain block B, B1, and B2. In another word, it retrieves multiple MV information of different CUs along some directions or some rules. The maximum distance of retrieved block can be limited within a range. For example, one, two, three CTU width and/or CTU height, or not exceed current CTU row.

FIG. 5 illustrates an exemplary flowchart of context-based adaptive binary arithmetic coding (CABAC) according to one embodiment of the present invention. The steps shown in the flowchart, as well as other flowcharts in this disclosure, may be implemented as program codes executable on one or more processors (e.g., one or more CPUs) at the encoder side and/or the decoder side. The steps shown in the flowchart may also be implemented based on hardware such as one or more electronic devices or processors arranged to perform the steps in the flowchart. According to this embodiment, context-adaptive arithmetic encoding or decoding is applied to a current bin of a binary data of a current coding symbol according to a current probability for a binary value of the current bin and a current range associated with the current state of the arithmetic coder, wherein the current probability is generated according to one or more previously coded symbols before the current coding symbol in step 510. For a video coding system, the coding symbols may correspond to transformed and quantized prediction residues, motion information for Inter predicted block, and various coding parameters such as coding modes. The coding symbols are binarized to generate a binary string. The CABAC coding may be applied to the binary string. An LPS probability index corresponding to an inverted current probability or the current probability is derived in step 520 depending on whether the current probability for the binary value of the current bin is greater than 0.5 (or 2^(k−1) if the current probability is represented by k-bit values). Various ways to derive the LPS probability index has been disclosed in this application. For example, if the current probability for the binary value of the current bin is greater than 0.5, an LPS (least-probably-symbol) probability is set equal to (1−the current probability) and otherwise, the LPS probability is set equal to the current probability; and the LPS probability index is determined based on a target index indicating one probability interval containing the current probability. A range index for identifying one range interval containing the current range is derived in step 530. An LPS range is derived either using one or more mathematical operations comprising calculating a multiplication of a first value related to (2*the LPS probability index+1) or the LPS probability index and a second value related to (2*a the range index+1) or the range index, or using a look-up-table including table contents corresponding to values of LPS range associated with a set of LPS probability indexes and a set of range indexes for encoding or decoding a binary value of the current bin in step 540, where the range index corresponds to a result of right-shifting the current range by mm and mm is a non-negative integer and each value of LPS range corresponds to one product of (2*one LPS probability index+1) and (2*one range index+1) or corresponds to a offset and one product of one LPS probability index and one range index.

The flowcharts shown are intended to illustrate an example of video coding according to the present invention. A person skilled in the art may modify each step, re-arranges the steps, split a step, or combine steps to practice the present invention without departing from the spirit of the present invention. In the disclosure, specific syntax and semantics have been used to illustrate examples to implement embodiments of the present invention. A skilled person may practice the present invention by substituting the syntax and semantics with equivalent syntax and semantics without departing from the spirit of the present invention.

The above description is presented to enable a person of ordinary skill in the art to practice the present invention as provided in the context of a particular application and its requirement. Various modifications to the described embodiments will be apparent to those with skill in the art, and the general principles defined herein may be applied to other embodiments. Therefore, the present invention is not intended to be limited to the particular embodiments shown and described, but is to be accorded the widest scope consistent with the principles and novel features herein disclosed. In the above detailed description, various specific details are illustrated in order to provide a thorough understanding of the present invention. Nevertheless, it will be understood by those skilled in the art that the present invention may be practiced.

Embodiment of the present invention as described above may be implemented in various hardware, software codes, or a combination of both. For example, an embodiment of the present invention can be one or more circuit circuits integrated into a video compression chip or program code integrated into video compression software to perform the processing described herein. An embodiment of the present invention may also be program code to be executed on a Digital Signal Processor (DSP) to perform the processing described herein. The invention may also involve a number of functions to be performed by a computer processor, a digital signal processor, a microprocessor, or field programmable gate array (FPGA). These processors can be configured to perform particular tasks according to the invention, by executing machine-readable software code or firmware code that defines the particular methods embodied by the invention. The software code or firmware code may be developed in different programming languages and different formats or styles. The software code may also be compiled for different target platforms. However, different code formats, styles and languages of software codes and other means of configuring code to perform the tasks in accordance with the invention will not depart from the spirit and scope of the invention.

The invention may be embodied in other specific forms without departing from its spirit or essential characteristics. The described examples are to be considered in all respects only as illustrative and not restrictive. The scope of the invention is therefore, indicated by the appended claims rather than by the foregoing description. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope. 

The invention claimed is:
 1. A method of entropy coding of coding symbols, the method comprising: applying context-adaptive arithmetic encoding or decoding to a current bin of a binary data of a current coding symbol according to a current binarized probability value of the current bin and a current range associated with a current state of the context-adaptive arithmetic encoding or decoding, wherein the current binarized probability value relates to a probability of the current bin generated according to one or more previously coded symbols before the current coding symbol; deriving an LPS probability index corresponding to an inverted current binarized probability value or the current binarized probability value, depending on whether the current binarized probability value of the current bin is greater than or equal to 2^(k−1), k being a positive integer; deriving a range index for identifying one range interval containing the current range; and deriving an LPS range using one or more mathematical operations comprising calculating a multiplication of a first value related to (2*the LPS probability index+1) or the LPS probability index and a second value related to (2*the range index+1) or the range index, or deriving the LPS range using a look-up-table including table contents corresponding to values of LPS range associated with a set of LPS probability indexes and a set of range indexes for encoding or decoding the current binarized probability value of the current bin, wherein the range index corresponds to a result of right-shifting the current range by mm and mm is a non-negative integer and each value of LPS range corresponds to one product of (2*one LPS probability index+1) and (2*one range index+1) or deriving an LPS range corresponds to an offset and one product of one LPS probability index and one range index.
 2. The method of claim 1, wherein when the probability for the current bin is greater than 0.5 or greater than or equal to 0.5, an LPS (least-probably-symbol) probability is set equal to (1−the current probability) and otherwise, the LPS probability is set equal to the probability; and the LPS probability index is determined based on a target index indicating one probability interval containing the probability or the LPS probability.
 3. The method of claim 1, wherein when the current binarized probability value of the current bin is greater than or equal to 2^(k−1), an LPS probability is set equal to (2^(k−1)−the current binarized probability value) and the LPS probability index is set equal to (2^(n+1)−1) minus a result of right-shifting the current binarized probability value by (k−n−1) bits; otherwise, the LPS probability is set equal to the current binarized probability value and the LPS probability index is set equal to the result of right-shifting the current binarized probability value by (k−n−1) bits, n and k are positive integers.
 4. The method of claim 1, wherein when the current binarized probability value of the current bin is greater than or equal to 2^(k−1), an LPS probability is set equal to (2^(k−1)−the current binarized probability value) and the LPS probability index is set equal to a result of right-shifting the LPS probability by (k−n−1) bits; otherwise, the LPS probability is set equal to the current binarized probability value and the LPS probability index is set equal to the result of right-shifting the current binarized probability value by (k−n−1) bits, n and k are positive integers.
 5. The method of claim 1, wherein k is equal to
 15. 6. The method of claim 4, wherein k is equal to 15, and n is equal to
 5. 7. The method of claim 3, wherein the LPS range is derived by multiplying (2*the LPS probability index+1) with (2*the range index+1) to obtain a multiplication result, and right-shifting the multiplication result by x bits and x is a positive integer.
 8. The method of claim 7, wherein x is equal to
 3. 9. The method of claim 3, wherein the LPS range is derived by multiplying the LPS probability index with the range index to obtain a multiplication result, and right-shifting the multiplication result by x bits plus an offset and x is a positive integer, the offset is an integer.
 10. The method of claim 9, wherein x is equal to 1, and the offset is equal to 2, 3, or
 4. 11. The method of claim 1, wherein the look-up-table corresponds to a two-dimensional table with the LPS probability index as a first table index in a first dimension and a clipped range index as a second table index in a second dimension, where the clipped range index corresponding to the range index.
 12. The method of claim 11, wherein the LPS probability index has a first value range from 0 to 31, the clipped range index has a second value range from 0 to 7 and the LPS range has a third value range from greater than or equal to 0 to smaller than or equal to
 255. 13. The method of claim 1, wherein the LPS probability is set equal to a result of bitwise exclusive or (XOR) for a value of (current probability>>(k−1)) and the current probability, or the LPS probability index is set equal to the result of bitwise exclusive or for the value of (current probability>>(k−1)) and the value of (current probability>>(k−n−1)); and wherein the current probability is represented by k-bit values, and n and k are positive integers.
 14. The method of claim 1, further comprising deriving, from the current range, a rangeOne value and a rangeZero value for the current bin having a value of one and a value of zero respectively, wherein if the current probability of the current bin is greater than 0.5 or is greater than or equal to 0.5, the rangeOne value is set to (the current range−the LPS range) and the rangeZero value is set to the LPS range; and otherwise, the rangeZero value is set to (the current range−the LPS range) and the rangeOne value is set to the LPS range.
 15. An entropy coding apparatus for an image or video encoder or decoder, the entropy coding apparatus comprising: apply context-adaptive arithmetic encoding or decoding to a current bin of a binary data of a current coding symbol according to a current binarized probability value of the current bin and a current range associated with a current state of the context-adaptive arithmetic encoding or decoding, wherein the current binarized probability value relates to a probability of the current bin generated according to one or more previously coded symbols before the current coding symbol; derive an LPS probability index corresponding to an inverted current binarized probability value or the current binarized probability value, depending on whether the current binarized probability value of the current bin is greater than or equal to 2^(k−1), k being a positive integer; derive a range index for identifying one range interval containing the current range; and derive an LPS range using one or more mathematical operations comprising calculating a multiplication of a first value related to (2*the LPS probability index+1) or the LPS probability index and a second value related to (2*the range index+1) or the range index, or deriving the LPS range using a look-up-table including table contents corresponding to values of LPS range associated with a set of LPS probability indexes and a set of range indexes for encoding or decoding the current binarized probability value of the current bin, wherein the range index corresponds to a result of right-shifting the current range by mm and mm is a non-negative integer and each value of LPS range corresponds to one product of (2*one LPS probability index+1) and (2*one range index+1) or derive an LPS range corresponds to an offset and one product of one LPS probability index and one range index.
 16. The entropy coding apparatus of claim 15, wherein when the probability for the current bin is greater than 0.5 or greater than or equal to 0.5, an LPS (least-probably-symbol) probability is set equal to (1−the current probability) and otherwise, the LPS probability is set equal to the probability; and the LPS probability index is determined based on a target index indicating one probability interval containing the probability or the LPS probability.
 17. The entropy coding apparatus of claim 15, wherein when the current binarized probability value of the current bin is greater than or equal to 2^(k−1), an LPS probability is set equal to (2^(k−1)−the current binarized probability value) and the LPS probability index is set equal to a result of right-shifting the LPS probability by (k−n−1) bits; otherwise, the LPS probability is set equal to the current binarized probability value and the LPS probability index is set equal to the result of right-shifting the current binarized probability value by (k−n−1) bits, n and k are positive integers.
 18. The entropy coding apparatus of claim 17, wherein the LPS range is derived by multiplying the LPS probability index with the range index to obtain a multiplication result, and right-shifting the multiplication result by x bits plus an offset and x is a positive integer, the offset is an integer.
 19. The entropy coding apparatus of claim 15, wherein the look-up-table corresponds to a two-dimensional table with the LPS probability index as a first table index in a first dimension and a clipped range index as a second table index in a second dimension, where the clipped range index corresponding to the range index.
 20. The entropy coding apparatus of claim 15, wherein the LPS probability is set equal to a result of bitwise exclusive or (XOR) for a value of (current probability>>(k−1)) and the current probability, or the LPS probability index is set equal to the result of bitwise exclusive or for the value of (current probability>>(k−1)) and the value of (current probability>>(k−n−1)); and wherein the current probability is represented by k-bit values, and n and k are positive integers. 